The firm relied on fragmented data from multiple custodians, making it difficult to maintain a consistent and accurate view of client portfolios. Advisors and operations teams spent significant time consolidating data from different sources before making investment decisions.

Portfolio rebalancing was largely manual and required teams to review holdings, identify portfolio drift, calculate required trades, and execute adjustments. This increased operational effort and created delays in responding to changing market conditions and client requirements.

Risk assessment and portfolio monitoring also lacked automation. Advisors had limited real-time visibility into portfolio risk, performance, and allocation changes, making proactive portfolio management more difficult.

Regulatory and compliance reporting required extensive manual preparation. Data had to be gathered, validated, and formatted across multiple systems, increasing reporting effort and reducing the time advisors could spend on client-facing activities.

The firm needed a scalable, AI-enabled portfolio management solution that could unify custodian data, automate rebalancing, improve risk intelligence, and deliver real-time investment visibility.